Teams at Menlo Inc.

Own humanoid robot deployments for enterprise customers from scoped use case through reliable operation on site. Build Python integrations, configure agents and safety constraints, validate tasks in simulation, deploy cloud or on-prem systems, and debug software, hardware, networking, and robot behavior. Train customer engineers, serve as the technical contact, and feed field learnings into product improvements, tooling, and deployment playbooks. Regular customer-site travel is required when hands-on robot support is needed.

Conduct end-to-end robot learning research for humanoid robots, developing generalist policies, imitation and reinforcement learning pipelines, autonomous data collection, and sim-to-real systems. Train vision-language-action models on real robot data, evaluate policies on hardware, and collaborate across locomotion, manipulation, world models, and platform teams. The role also involves publishing research, open-sourcing work, and building self-improvement loops for continuous learning.

Design, train, and deploy reinforcement and imitation learning policies for humanoid robots. Run physical robot experiments, improve sim-to-real transfer, maintain simulation environments and data pipelines, analyze deployment failures, and collaborate with hardware and firmware teams to improve policy robustness.